HADOOP AND NOSQL INTEGRATION

Leverage Streaming Data Integration to Get More from Big Data

GAIN MORE VALUE FROM HADOOP AND NOSQL WITH A STREAMING DATA ARCHITECTURE

Big Data Lakes are often a random collection of large volumes of data for uncertain use cases. Because of this, many Big Data solutions struggle to keep up with large data volumes and the need to drive clear value. With batch integration and after-the-fact analytics, Big Data solutions cannot discover urgent and perishable operational insights. Using streaming data integration, you can ingest real-time data from a wide range of sources and pre-process it in-flight to enable operational use cases and accelerate insight.

Gain more operational value from Hadoop and NoSQL by using low-latency data

Transform and enrich data in motion before delivering to Hadoop and NoSQL without introducing latency

Extend the lifetime of existing Hadoop and NoSQL solutions by storing only the data you need

Feed real-time training data to machine learning (ML) solutions and use ML models on real-time events to support operational decision making

AEROSPACE MANUFACTURER

The leading aerospace and defense manufacturer chose Striim to support its modernization of analytics solutions. The company moved to a Hadoop-based Big Data environment to provide richer and more timely analytics to its employees and partners. Striim integrates its HP NonStop OLTP systems with their Hadoop ecosystem by delivering transactional data to HDFS, Kafka, and HBase in real time. With the ability to contain up-to-date airplane parts and schema data in the Hadoop environment, the company moved operational reporting processes from HP NonStop to Hadoop.